Empirical comparison of routinely collected electronic health record data for head and neck cancer-specific survival in machine-learnt prognostic models.

Kotevski, Damian P; Smee, Robert I; Vajdic, Claire M; Field, Matthew

Kotevski, Damian P; Smee, Robert I; Vajdic, Claire M; Field, Matthew.

Afiliación

Kotevski DP; Department of Radiation Oncology, Prince of Wales Hospital and Community Health Services, Sydney, New South Wales, Australia.
Smee RI; Prince of Wales Clinical School, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia.
Vajdic CM; Department of Radiation Oncology, Prince of Wales Hospital and Community Health Services, Sydney, New South Wales, Australia.
Field M; Prince of Wales Clinical School, Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia.

Head Neck ; 45(2): 365-379, 2023 02.

Article en En | MEDLINE | ID: mdl-36369773

Asunto(s)

Carcinoma de Células Escamosas; Neoplasias de Cabeza y Cuello; Adulto; Humanos; Pronóstico; Registros Electrónicos de Salud; Neoplasias de Cabeza y Cuello/terapia; Carcinoma de Células Escamosas/terapia

Palabras clave

cancer-specific survival; head and neck cancer; machine learning; prediction models; prognostic factors

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Carcinoma de Células Escamosas / Neoplasias de Cabeza y Cuello Tipo de estudio: Prognostic_studies Límite: Adult / Humans Idioma: En Revista: Head Neck Asunto de la revista: NEOPLASIAS Año: 2023 Tipo del documento: Article País de afiliación: Australia Pais de publicación: Estados Unidos

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